2020 USGS Lidar: Goodhue County, MN
Data Set (DS) | OCM Partners (OCMP)GUID: gov.noaa.nmfs.inport:72333 | Updated: July 31, 2024 | Published / External
Summary
Short Citation
OCM Partners, 2024: 2020 USGS Lidar: Goodhue County, MN, https://www.fisheries.noaa.gov/inport/item/72333.
Full Citation Examples
Project Description for the Original Data:
The Goodhue County lidar project area covers approximately 941 square miles which includes a 100 meter buffer around the county boundary. The airborne lidar data was acquired at an aggregate nominal point density (ANPD) of 30 points per square meter. Project specifications are based on Goodhue County requirements and on the U.S. Geological Survey National Geospatial Program LiDAR Base Specification, Version 2.1. The data was developed based on a horizontal projection/datum of NAD83(HARN) Adj MN Goodhue Co (ftUS), and vertical datum of NAVD88 - Geoid12B (Feet). LiDAR data was acquired using a Riegl VQ 1560i sensor with serial number 4040 from April 08, 2020 to May 03, 2020 in 13 total lifts. Acquisition occurred with leaves absent from deciduous trees, when no snow was present on the ground, and with rivers at or below normal levels.
This metadata record supports the data entry in the NOAA Digital Coast Data Access Viewer (DAV). For this data set, the DAV is leveraging the Entwine Point Tiles (EPT) hosted by USGS on Amazon Web Services.
Distribution Information
-
Not Applicable
Create custom data files by choosing data area, product type, map projection, file format, datum, etc. A new metadata will be produced to reflect your request using this record as a base. Change to an orthometric vertical datum is one of the many options.
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LAS/LAZ - LASer
Bulk download of data files in LAZ format, in the original, as collected, coordinates and in orthometric (Geoid 12b) elevations in feet.
None
Users should be aware that temporal changes may have occurred since this data set was collected and some parts of this data may no longer represent actual surface conditions. Users should not use this data for critical applications without a full awareness of its limitations.
Controlled Theme Keywords
EARTH SCIENCE, elevation, TERRAIN ELEVATION
Child Items
No Child Items for this record.
Contact Information
Point of Contact
NOAA Office for Coastal Management (NOAA/OCM)
coastal.info@noaa.gov
(843) 740-1202
https://coast.noaa.gov
Metadata Contact
NOAA Office for Coastal Management (NOAA/OCM)
coastal.info@noaa.gov
(843) 740-1202
https://coast.noaa.gov
Extents
-93.097105° W,
-92.220453° E,
44.721758° N,
44.165595° S
2020-04-08 - 2020-05-03
Dates of collection for Goodhue County
Item Identification
Title: | 2020 USGS Lidar: Goodhue County, MN |
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Short Name: | mn2020_goodhue_m10100_metadata |
Status: | Completed |
Creation Date: | 2020 |
Publication Date: | 2020-06-23 |
Abstract: |
Project Description for the Original Data: The Goodhue County lidar project area covers approximately 941 square miles which includes a 100 meter buffer around the county boundary. The airborne lidar data was acquired at an aggregate nominal point density (ANPD) of 30 points per square meter. Project specifications are based on Goodhue County requirements and on the U.S. Geological Survey National Geospatial Program LiDAR Base Specification, Version 2.1. The data was developed based on a horizontal projection/datum of NAD83(HARN) Adj MN Goodhue Co (ftUS), and vertical datum of NAVD88 - Geoid12B (Feet). LiDAR data was acquired using a Riegl VQ 1560i sensor with serial number 4040 from April 08, 2020 to May 03, 2020 in 13 total lifts. Acquisition occurred with leaves absent from deciduous trees, when no snow was present on the ground, and with rivers at or below normal levels. This metadata record supports the data entry in the NOAA Digital Coast Data Access Viewer (DAV). For this data set, the DAV is leveraging the Entwine Point Tiles (EPT) hosted by USGS on Amazon Web Services. |
Purpose: |
This data, along with its derivatives, is the result of a countywide elevation mapping with cooperative partnerships from Goodhue County, Minnesota DOA, and the USGS 3DEP program. This data was produced from lidar data collected in May 2020, which was processed and delivered in 2020. |
Supplemental Information: |
The following are the USGS lidar fields in JSON: {
"ldrinfo" : {
"ldrspec" : "National Geospatial Program (NGP) Lidar Base Specification v2.1", "ldrsens" : "Riegl VQ 1560i_SN4040", "ldrmaxnr" : "7", "ldrnps" : "0.337", "ldrdens" : "30.0", "ldranps" : "0.335", "ldradens" : "30.0", "ldrfltht" : "1200", "ldrfltsp" : "180", "ldrscana" : "58.5", "ldrscanr" : "388", "ldrpulsr" : "2000", "ldrpulsd" : "30", "ldrpulsw" : "1344", "ldrwavel" : "194", "ldrmpia" : "1", "ldrbmdiv" : "1", "ldrswatw" : "1121", "ldrswato" : "60", "ldrgeoid" : "National Geodetic Survey (NGS) Geoid12B" }, "ldraccur" : {
"ldrchacc" : "0", "rawnva" : "0", "rawnvan" : "0" }, "lasinfo" : {
"lasver" : "1.4", "lasprf" : "6", "laswheld" : "Withheld (ignore) points were identified in these files using the standard LAS Withheld bit.", "lasolap" : "Swath "overage" points were identified in these files using the standard LAS overlap bit.", "lasintr" : "11", "lasclass" : {
"clascode" : "1", "clasitem" : "Processed, but Unclassified" }, "lasclass" : {
"clascode" : "2", "clasitem" : "Bare Earth Ground" }, "lasclass" : {
"clascode" : "5", "clasitem" : "High Vegetation" }, "lasclass" : {
"clascode" : "6", "clasitem" : "Buildings" }, "lasclass" : {
"clascode" : "7", "clasitem" : "Low Noise" }, "lasclass" : {
"clascode" : "9", "clasitem" : "Water" }, "lasclass" : {
"clascode" : "17", "clasitem" : "Bridge Deck" }, "lasclass" : {
"clascode" : "18", "clasitem" : "High Noise" }, "lasclass" : { "clascode" :["20","Ignored Ground","22"," Temporal Exclusion"] } }} |
Keywords
Theme Keywords
Thesaurus | Keyword |
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Global Change Master Directory (GCMD) Science Keywords |
EARTH SCIENCE
|
Global Change Master Directory (GCMD) Science Keywords |
EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION
|
ISO 19115 Topic Category |
elevation
|
Spatial Keywords
Thesaurus | Keyword |
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Global Change Master Directory (GCMD) Location Keywords |
CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA
|
Global Change Master Directory (GCMD) Location Keywords |
CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > MINNESOTA
|
Global Change Master Directory (GCMD) Location Keywords |
VERTICAL LOCATION > LAND SURFACE
|
Instrument Keywords
Thesaurus | Keyword |
---|---|
Global Change Master Directory (GCMD) Instrument Keywords |
LIDAR > Light Detection and Ranging
|
Platform Keywords
Thesaurus | Keyword |
---|---|
Global Change Master Directory (GCMD) Platform Keywords |
Airplane > Airplane
|
Physical Location
Organization: | Office for Coastal Management |
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City: | Charleston |
State/Province: | SC |
Data Set Information
Data Set Scope Code: | Data Set |
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Data Set Type: | Elevation |
Maintenance Frequency: | None Planned |
Data Presentation Form: | Model (digital) |
Distribution Liability: |
Any conclusions drawn from the analysis of this information are not the responsibility of NOAA, the Office for Coastal Management or its partners. |
Data Set Credit: | Ayres Associates, USGS |
Support Roles
Data Steward
Date Effective From: | 2024 |
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Date Effective To: | |
Contact (Organization): | NOAA Office for Coastal Management (NOAA/OCM) |
Address: |
2234 South Hobson Ave Charleston, SC 29405-2413 |
Email Address: | coastal.info@noaa.gov |
Phone: | (843) 740-1202 |
URL: | https://coast.noaa.gov |
Distributor
Date Effective From: | 2024 |
---|---|
Date Effective To: | |
Contact (Organization): | NOAA Office for Coastal Management (NOAA/OCM) |
Address: |
2234 South Hobson Ave Charleston, SC 29405-2413 |
Email Address: | coastal.info@noaa.gov |
Phone: | (843) 740-1202 |
URL: | https://coast.noaa.gov |
Distributor
Date Effective From: | 2022 |
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Date Effective To: | |
Contact (Organization): | U.S. Geological Survey |
Address: |
12201 Sunrise Valley Drive Reston, VA 20191 USA |
URL: | USGS Home |
Metadata Contact
Date Effective From: | 2024 |
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Date Effective To: | |
Contact (Organization): | NOAA Office for Coastal Management (NOAA/OCM) |
Address: |
2234 South Hobson Ave Charleston, SC 29405-2413 |
Email Address: | coastal.info@noaa.gov |
Phone: | (843) 740-1202 |
URL: | https://coast.noaa.gov |
Point of Contact
Date Effective From: | 2024 |
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Date Effective To: | |
Contact (Organization): | NOAA Office for Coastal Management (NOAA/OCM) |
Address: |
2234 South Hobson Ave Charleston, SC 29405-2413 |
Email Address: | coastal.info@noaa.gov |
Phone: | (843) 740-1202 |
URL: | https://coast.noaa.gov |
Extents
Currentness Reference: | Ground Condition |
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Extent Group 1
Extent Group 1 / Geographic Area 1
W° Bound: | -93.097105 | |
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E° Bound: | -92.220453 | |
N° Bound: | 44.721758 | |
S° Bound: | 44.165595 |
Extent Group 1 / Time Frame 1
Time Frame Type: | Range |
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Start: | 2020-04-08 |
End: | 2020-05-03 |
Description: |
Dates of collection for Goodhue County |
Spatial Information
Spatial Representation
Representations Used
Grid: | No |
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Vector: | Yes |
Text / Table: | No |
TIN: | No |
Stereo Model: | No |
Video: | No |
Vector Representation 1
Point Object Present?: | Yes |
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Point Object Count: | 183448445150 |
Reference Systems
Reference System 1
Coordinate Reference System |
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Reference System 2
Coordinate Reference System |
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Access Information
Security Class: | Unclassified |
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Data Access Procedure: |
Data is available online for bulk and custom downloads. |
Data Access Constraints: |
None |
Data Use Constraints: |
Users should be aware that temporal changes may have occurred since this data set was collected and some parts of this data may no longer represent actual surface conditions. Users should not use this data for critical applications without a full awareness of its limitations. |
Distribution Information
Distribution 1
Start Date: | 2024-03-19 |
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End Date: | Present |
Download URL: | https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=10100/details/10100 |
Distributor: | NOAA Office for Coastal Management (NOAA/OCM) (2024 - Present) |
File Name: | Customized Download |
Description: |
Create custom data files by choosing data area, product type, map projection, file format, datum, etc. A new metadata will be produced to reflect your request using this record as a base. Change to an orthometric vertical datum is one of the many options. |
Distribution Format: | Not Applicable |
Compression: | Zip |
Distribution 2
Start Date: | 2022 |
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End Date: | Present |
Download URL: | https://rockyweb.usgs.gov/vdelivery/Datasets/Staged/Elevation/LPC/Projects/MN_GoodhueCounty_2020_A20/MN_GoodhueCo_1_2020/LAZ/ |
Distributor: | U.S. Geological Survey (2022 - Present) |
File Name: | Bulk Download |
Description: |
Bulk download of data files in LAZ format, in the original, as collected, coordinates and in orthometric (Geoid 12b) elevations in feet. |
Distribution Format: | LAS/LAZ - LASer |
Compression: | LAZ |
URLs
URL 1
URL: | https://coast.noaa.gov/dataviewer/ |
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Name: | NOAA's Office for Coastal Management (OCM) Data Access Viewer (DAV) |
URL Type: |
Online Resource
|
File Resource Format: | HTML |
Description: |
The Data Access Viewer (DAV) allows a user to search for and download elevation, imagery, and land cover data for the coastal U.S. and its territories. The data, hosted by the NOAA Office for Coastal Management, can be customized and requested for free download through a checkout interface. An email provides a link to the customized data, while the original data set is available through a link within the viewer. |
URL 2
URL: | https://s3-us-west-2.amazonaws.com/usgs-lidar-public/MN_GoodhueCo_1_2020/ept.json |
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Name: | USGS Entwine Point Tile (EPT) |
URL Type: |
Online Resource
|
File Resource Format: | json |
Description: |
Entwine Point Tile (EPT) is a simple and flexible octree-based storage format for point cloud data. The data is organized in such a way that the data can be reasonably streamed over the internet, pulling only the points you need. EPT files can be queried to return a subset of the points that give you a representation of the area. As you zoom further in, you are requesting higher and higher densities. A dataset in EPT will contain a lot of files, however, the ept.json file describes all the rest. The EPT file can be used in Potree and QGIS to view the point cloud. |
URL 3
URL: | https://usgs.entwine.io/data/view.html?r=https://s3-us-west-2.amazonaws.com/usgs-lidar-public/MN_GoodhueCo_1_2020/ept.json |
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Name: | USGS 3D View |
URL Type: |
Online Resource
|
Description: |
Link to view the point cloud, using the Entwine Point Tile (EPT) format, in the 3D Potree viewer. |
URL 4
URL: | https://prd-tnm.s3.amazonaws.com/StagedProducts/Elevation/metadata/MN_GoodhueCounty_2020_A20/MN_GoodhueCo_1_2020/reports/Processing%20Report%20Goodhue%20County%203DEP%20Lidar_Ayres.pdf |
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Name: | Lidar Processing Report |
File Resource Format: | |
Description: |
Link to the Ayres lidar processing report. |
URL 5
URL: | https://prd-tnm.s3.amazonaws.com/StagedProducts/Elevation/metadata/MN_GoodhueCounty_2020_A20/MN_GoodhueCo_1_2020/reports/Collection%20Report%20Goodhue%20County%203DEP%20Lidar_Ayres.pdf |
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Name: | Lidar Collection Report |
URL Type: |
Online Resource
|
File Resource Format: | |
Description: |
Link to the Ayres lidar collection report. |
URL 6
URL: | https://prd-tnm.s3.amazonaws.com/StagedProducts/Elevation/metadata/MN_GoodhueCounty_2020_A20/USGS_MN_GoodhueCounty_2020_A20_ProjectReport.pdf |
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Name: | USGS Project Report |
URL Type: |
Online Resource
|
File Resource Format: | |
Description: |
Link to the USGS Project Report that provides information about the project, vertical accuracy results, and the point classes and sensors used. |
URL 7
URL: | https://prd-tnm.s3.amazonaws.com/index.html?prefix=StagedProducts/Elevation/metadata/MN_GoodhueCounty_2020_A20/MN_GoodhueCo_1_2020/ |
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Name: | USGS Additional Info |
URL Type: |
Online Resource
|
Description: |
Link to the reports, breaklines, metadata, and spatial metadata. |
Technical Environment
Description: |
Terrasolid |
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Data Quality
Vertical Positional Accuracy: |
This data set was produced to meet ASPRS Positional Accuracy Standard for Digital Geospatial Data (2014) for a 10-cm RMSEz Vertical Accuracy Class. USGS Determined Vertical Accuracy: Tested NVA RMSEz = 2.77 cm Tested 95th percentile value for VVA is : 12.20 cm For more information see the USGS project report and the lidar report. The links to these reports are provided in the URL section of this metadata record. |
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Completeness Report: |
These LAS data files include all data points collected. No points have been removed or excluded. A visual qualitative assessment was performed to ensure data completeness. No void areas or missing data exist. The raw point cloud is complete and data passes Vertical Accuracy specifications. |
Conceptual Consistency: |
Data covers the entire area specified for this project. |
Data Management
Have Resources for Management of these Data Been Identified?: | Yes |
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Approximate Percentage of Budget for these Data Devoted to Data Management: | Unknown |
Do these Data Comply with the Data Access Directive?: | Yes |
Actual or Planned Long-Term Data Archive Location: | NCEI-NC |
How Will the Data Be Protected from Accidental or Malicious Modification or Deletion Prior to Receipt by the Archive?: |
Data is backed up to cloud storage. |
Lineage
Lineage Statement: |
The NOAA Office for Coastal Management (OCM) ingested references to the USGS Entwine Point Tiles (EPT) hosted on Amazon Web Services (AWS) into the Digital Coast Data Access Viewer (DAV). The DAV accesses the point cloud as it resides on AWS under the usgs-lidar-public-container. |
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Sources
USGS AWS Entwine Point Tile (EPT) - MN_GoodhueCo_1_2020
Contact Role Type: | Publisher |
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Contact Type: | Organization |
Contact Name: | USGS |
Citation URL: | https://s3-us-west-2.amazonaws.com/usgs-lidar-public/MN_GoodhueCo_1_2020/ept.json |
Citation URL Name: | Entwine Point Tile (EPT) for MN_GoodhueCo_1_2020 |
Process Steps
Process Step 1
Description: |
The boresight for each lift was done individually as the solution may change slightly from lift to lift. The following steps describe the Raw Data Processing and Boresight process: 1) Technicians processed the raw data to LAS format flight lines using the final GPS/IMU solution. This LAS data set was used as source data for boresight. 2) Technicians first used RIEGL RiPROCESS software to calculate initial boresight adjustment angles based on sample areas selected in the lift. These areas cover calibration flight lines collected in the lift, cross tie and production flight lines. These areas are well distributed in the lift coverage and cover multiple terrain types that are necessary for boresight angle calculation. The technician then analyzed the results and made any necessary additional adjustment until it is acceptable for the selected areas. 3) Once the boresight angle calculation was completed for the selected areas, the adjusted settings were applied to all of the flight lines of the lift and checked for consistency. The technicians utilized commercial and proprietary software packages to analyze how well flight line overlaps match for the entire lift and adjusted as necessary until the results met the project specifications. 4) Once all lifts were completed with individual boresight adjustment, the technicians checked and corrected the vertical misalignment of all flight lines and also the matching between data and ground truth. The relative accuracy was less than or equal to 7 cm RMSEz within individual swaths and less than or equal to 10 cm RMSEz or within swath overlap (between adjacent swaths). 5) The technicians ran a final vertical accuracy check of the boresighted flight lines against the surveyed check points after the z correction to ensure the requirement of NVA = 9.8 cm 95% Confidence Level (Required Accuracy) was met. Point classification was performed according to USGS Lidar Base Specification 2.1, and breaklines were collected for water features. Bare earth DEMs were exported from the classified point cloud using collected breaklines for hydroflattening. |
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Process Date/Time: | 2020-06-23 00:00:00 |
Process Step 2
Description: |
LAS Point Cloud Classification: LiDAR data processing for the point cloud deliverable consists of classifying the LiDAR using a combination of automated classification and manual edit/reclassification processes. On most projects the automated classification routines will correctly classify 90-95 percent of the LiDAR points. The remaining 5-10 percent of the bare earth ground class must undergo manual edit and reclassification. Because the classified points serve as the foundation for the Terrain, DEM and breakline products, it is necessary for the QA/QC supervisor to review the completed point cloud deliverables prior to the production of any additional products. The following workflow steps are followed for automated LiDAR classification: 1. Lead technicians review the group of LiDAR tiles to determine which automated classification routines will achieve the best results. Factors such as vegetation density, cultural features, and terrain can affect the accuracy of the automated classification. The lead technicians have the ability to edit or tailor specific routines in order to accommodate the factors mentioned above, and achieve the best results and address errors. 2. Distributive processing is used to maximize the available hardware resources and speed up the automated processing as this is a resource-intensive process. 3. Once the results of the automated classification have been reviewed and passed consistent checks, the supervisor then approves the data tiles for manual classification. The following workflow steps are followed for manual edits of the LiDAR bare earth ground classification: 1. LiDAR technicians review each tile for errors made by the automated routines and correctly address errors any points that are in the wrong classification. By methodically panning through each tile, the technicians view the LiDAR points in profile, with a TIN surface, and as a point cloud. 2. Any ancillary data available, such as Google Earth, is used to identify any features that may not be identifiable as points so that the technician can make the determination to which classification the feature belongs. The QA/QC processes for the LiDAR processing phase consist of: 1. The lead technician reviews all automated classification results and adjust the macros as necessary to achieve the optimal efficiency. This is an iterative process, and the technician may need to make several adjustments to the macros, depending upon the complexity of the features in the area being processed. During the manual editing process, the LiDAR technicians use a system of QA, whereby they check each other’s edits. This results in several benefits to the process: There is a greater chance of catching minor blunders It increases communication between technicians on technique and appearance Solutions to problems are communicated efficiently To ensure consistency across the project area, the supervisor reviews the data once the manual editing is complete. For this phase of a project, the following specifications are checked against: • Point cloud – all points must be classified according to the USGS classification standard for LAS. The all-return point cloud must be delivered in fully-compliant LAS version 1.4. • LAS files will use the Spatial Reference Framework according to project specification and all files shall be projected and defined. • General Point classifications: Class 1. Processed, but unclassified Class 2. Bare Earth Class 5. High Vegetation Class 6. Building Class 7. Noise Class 9. Water Class 17. Bridge Decks Class 18. High Noise Class 20. Ignored ground (Breakline proximity) Class 22. Temporaral Exclusion • Outliers, noise, blunders, duplicates, geometrically unreliable points near the extreme edge of the swath, and other points deemed unusable are to be identified using the "Withheld" flag. This applies primarily to points which are identified during pre-processing or |
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Process Date/Time: | 2020-06-23 00:00:00 |
Process Step 3
Description: |
Original point clouds in LAS/LAZ format were restructured as Entwine Point Tiles and stored on Amazon Web Services. The data were re-projected horizontally to WGS84 web mercator (EPSG 3857) and the vertical units were converted to meters (NAVD88 Geoid12B). |
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Process Contact: | U.S. Geological Survey |
Process Step 4
Description: |
The NOAA Office for Coastal Management (OCM) created references to the Entwine Point Tiles (EPT) that were ingested into the NOAA Digital Coast Data Access Viewer (DAV). No changes were made to the data. The DAV will access the point cloud as it resides on Amazon Web Services (AWS) under the usgs-lidar-public container. This is the AWS URL being accessed: https://s3-us-west-2.amazonaws.com/usgs-lidar-public/MN_GoodhueCo_1_2020/ept.json |
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Process Date/Time: | 2024-03-19 00:00:00 |
Process Contact: | Office for Coastal Management (OCM) |
Catalog Details
Catalog Item ID: | 72333 |
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GUID: | gov.noaa.nmfs.inport:72333 |
Metadata Record Created By: | Rebecca Mataosky |
Metadata Record Created: | 2024-03-19 21:47+0000 |
Metadata Record Last Modified By: | Rebecca Mataosky |
Metadata Record Last Modified: | 2024-07-31 18:30+0000 |
Metadata Record Published: | 2024-03-20 |
Owner Org: | OCMP |
Metadata Publication Status: | Published Externally |
Do Not Publish?: | N |
Metadata Last Review Date: | 2024-03-20 |
Metadata Review Frequency: | 1 Year |
Metadata Next Review Date: | 2025-03-20 |